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inference.py
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/
inference.py
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#!/usr/bin/env python3
"""
Copyright (c) 2018 Intel Corporation.
Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
the following conditions:
The above copyright notice and this permission notice shall be
included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE
LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
"""
import os
import sys
import logging as log
from openvino.inference_engine import IENetwork, IECore
class Network:
"""
Load and configure inference plugins for the specified target devices
and performs synchronous and asynchronous modes for the specified infer requests.
"""
def __init__(self):
#Initialize any class variables desired ###
self.plugin = None
self.network = None
self.input_blob = None
self.output_blob = None
self.exec_network = None
def load_model(self, model, device, cpu_extension):
model_xml = model
model_weights = model.split('.')[0] + ".bin"
#Load the model ###
self.plugin = IECore()
self.network = IENetwork(model = model_xml, weights = model_weights)
#Check for supported layers ###
supported_layers = self.plugin.query_network(network = self.network, device_name = device)
#Add any necessary extensions ###
if cpu_extension and 'CPU' in device:
self.plugin.add_extension(cpu_extension, "CPU")
### TODO: Return the loaded inference plugin ###
unsupported_layers = [test_layer for test_layer in self.network.layers.keys() if test_layer not in supported_layers]
self.exec_network = self.plugin.load_network(self.network, device)
self.input_blob = next(iter(self.network.inputs))
self.output_blob = next(iter(self.network.outputs))
return
def get_input_shape(self):
#Return the shape of the input layer ###
return self.network.inputs[self.input_blob].shape
def exec_net(self, image, request_id):
#Start an asynchronous request ###
request_handler = self.exec_network.start_async(request_id = request_id, inputs = {self.input_blob: image})
return self.exec_network
def wait(self, request_id):
#Wait for the request to be complete. ###
return self.exec_network.requests[request_id].wait(-1)
def get_output(self, request_id):
#Extract and return the output results
return self.exec_network.requests[request_id].outputs[self.output_blob]